Knowledge Representation (Special Issues of Artificial Intelligence)

Knowledge Representation (Special Issues of Artificial Intelligence)

By: Hector J. Levesque (editor), Ronald J. Brachman (editor), Raymond Reiter (editor), etc. (editor)Hardback

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Description

Growing interest in symbolic representation and reasoning has pushed this backstage activity into the spotlight as a clearly identifiable and technically rich subfield in artificial intelligence. This collection of extended versions of 12 papers from the First International Conference on Principles of Knowledge Representation and Reasoning provides a snapshot of the best current work in AI on formal methods and principles of representation and reasoning. The topics range from temporal reasoning to default reasoning to representations for natural language.Ronald J. Brachman is Head of the Artificial Intelligence Principles Research Department at AT&T Bell Laboratories. Hector J. Levesque and Raymond Reiter are Professors of Computer Science at the University of Toronto.Contents: Introduction. Nonmonotonic Reasoning in the Framework of Situation Calculus. The Computational Complexity of Abduction. Temporal Constraint Networks. Impediments to Universal Preference-Based Default Theories. Embedding Decision-Analytic Control in a Learning Architecture. The Substitutional Framework for Sorted Deduction: Fundamental Results on Hybrid Reasoning. Existence Assumptions in Knowledge Representation. Hard Problems for Simple Default Logics. The Effect of Knowledge on Belief: Conditioning, Specificity and the Lottery Paradox in Default Reasoning. Three-Valued Nonmonotonic Formalisms and Semantics of Logic Programs. On the Applicability of Nonmonotonic Logic to Formal Reasoning in Continuous Time. Principles of Metareasoning.

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About Author

Ronald J. Brachman is Head of the Artificial Intelligence Principles Research Department at AT&T Bell Laboratories. Hector J. Levesque is Professor of Computer Science at the University of Toronto. He is the coauthor (with Gerhard Lakemeyer) of The Logic of Knowledge Bases (MIT Press, 2001) and coeditor (with Ronald J. Brachman) of Knowledge Representation and Reasoning (MIT Press, 1992). Raymond Reiter is Professor and Co-Director of the Cognitive Robotics Project in the Department of Computer Science at the University of Toronto.

Contents

Introduction to special volume on knowledge representation, R.J. Brachman et al; nonmonotonic reasoning in the framework of situation calculus, A.B. Baker; the computational complexity of abduction, T. Bylander et al; temporal constraint networks, R. Dechter et al; impediments to universal preference-based default theories, J. Doyle and M.P. Wellman; embedding decision-analytic control in a learning architecture, O. Etzioni; the substitutional framework for sorted deduction - fundamental results on hybrid reasoning, A.M. Frisch; existence assumptions in knowledge representation, G. Hirst; hard problems for simple default logics, H.A. Kautz and B. Selman; the effect of knowledge on belief - conditioning, specificity and the lottery paradox in default reasoning, D. Poole; three-valued nonmonotonic formalisms and the semantics of logic programs, T. Przymusinski; on the applicability of nonmonotonic logic to formal reasoning in continuous time, M. Rayner; principles of metareasoning, S. Russell and E. Wefald.

Product Details

  • publication date: 02/04/1992
  • ISBN13: 9780262521680
  • Format: Hardback
  • Number Of Pages: 414
  • ID: 9780262521680
  • weight: 839
  • ISBN10: 0262521687

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